Environments with multi-sensors are becoming widely used in order to separate signals originating from mixing environments, that have more than one signal source, such as conference rooms and offices with air conditioning, computers and people creating audio signals.
Separation of multiple signals from their superposition recorded at several sensors is an important problem that shows up in a variety of applications such as communications, biomedical and speech processing. The separation task is made difficult by the fact that very little is known about the input signals and thus the separation is commonly referred to as blind signal separation as describe in Zhang and A. Cichocki, “Blind Deconvolution of Dynamical Systems: A State Space Approach’, Journal of Signal Processing, vol. 4, No. 2, March 2000, pp. 111-130.
In WO9858450 there is described a method and apparatus for signal separation of a mixed signal originating from a waveform mixing environment. The method and apparatus use blind signal separation and is only applicable to a mixing environment where the number of associated sensors remains constant.
In WO0176319 there is also described a method and apparatus for signal separation of a mixed signal originating from a waveform mixing environment. The method and apparatus use sensor array technology with predetermined microphone positions and is only applicable to a mixing environment where the number of associated sensors remains constant and stationary.
Ideally, the number of sensor should be at least equal to, if not greater than, the number of signals sources in order to effectively provide effective waveform separation. Thus, static separation systems with having a constant number of sensors are not suitable for dynamic environments in which the maximum number of signals sources cannot be determined.
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